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We present a combinatorial algorithm for the general topological simplification of scalar fields on surfaces. Given a scalar field f, our algorithm generates a simplified field g that provably admits only critical points from a constrained subset of the singularities of f, while guaranteeing a small distance ||f - g||∞ for data-fitting purpose. In contrast to previous algorithms, our approach is oblivious to the strategy used for selecting features of interest and allows critical points to be removed arbitrarily. When topological persistence is used to select the features of interest, our algorithm produces a standard ϵ-simplification. Our approach is based on a new iterative algorithm for the constrained reconstruction of sub- and sur-level sets. Extensive experiments show that the number of iterations required for our algorithm to converge is rarely greater than 2 and never greater than 5, yielding O(n log(n)) practical time performances. The algorithm handles triangulated surfaces with or without boundary and is robust to the presence of multi-saddles in the input. It is simple to implement, fast in practice and more general than previous techniques. Practically, our approach allows a user to arbitrarily simplify the topology of an input function and robustly generate the corresponding simplified function. An appealing application area of our algorithm is in scalar field design since it enables, without any threshold parameter, the robust pruning of topological noise as selected by the user. This is needed for example to get rid of inaccuracies introduced by numerical solvers, thereby providing topological guarantees needed for certified geometry processing. Experiments show this ability to eliminate numerical noise as well as validate the time efficiency and accuracy of our algorithm. We provide a lightweight C++ implementation as supplemental material that can be used for topological cleaning on surface meshes.

Creating high-quality quad meshes from triangulated surfaces is a highly nontrivial task that necessitates consideration of various application specific metrics of quality. In our work, we follow the premise that automatic reconstruction techniques may not generate outputs meeting all the subjective quality expectations of the user. Instead, we put the user at the center of the process by providing a flexible, interactive approach to quadrangulation design. By combining scalar field topology and combinatorial connectivity techniques, we present a new framework, following a coarse to fine design philosophy, which allows for explicit control of the subjective quality criteria on the output quad mesh, at interactive rates. Our quadrangulation framework uses the new notion of Reeb atlas editing, to define with a small amount of interactions a coarse quadrangulation of the model, capturing the main features of the shape, with user prescribed extraordinary vertices and alignment. Fine grain tuning is easily achieved with the notion of connectivity texturing, which allows for additional extraordinary vertices specification and explicit feature alignment, to capture the high-frequency geometries. Experiments demonstrate the interactivity and flexibility of our approach, as well as its ability to generate quad meshes of arbitrary resolution with high-quality statistics, while meeting the user’s own subjective requirements.

In this paper, we characterize the range of features that can be extracted from an Morse-Smale complex and describe a unified query language to extract them. We provide a visual dictionary to guide users when defining features in terms of these queries. We demonstrate our topology-rich visualization pipeline in a tool that interactively queries the MS complex to extract features at multiple resolutions, assigns rendering attributes, and combines traditional volume visualization with the extracted features. The flexibility and power of this approach is illustrated with examples showing novel features.

Robust analysis of vector fields has been established as an important tool for deriving insights from the complex systems these fields model. Traditional analysis and visualization techniques rely primarily on computing streamlines through numerical integration. The inherent numerical errors of such approaches are usually ignored, leading to inconsistencies that cause unreliable visualizations and can ultimately prevent in-depth analysis. We propose a new representation for vector fields on surfaces that replaces numerical integration through triangles with maps from the triangle boundaries to themselves. This representation, called edge maps, permits a concise description of flow behaviors and is equivalent to computing all possible streamlines at a user defined error threshold. Independent of this error streamlines computed using edge maps are guaranteed to be consistent up to floating point precision, enabling the stable extraction of features such as the topological skeleton. Furthermore, our representation explicitly stores spatial and temporal errors which we use to produce more informative visualizations. This work describes the construction of edge maps, the error quantification, and a refinement procedure to adhere to a user defined error bound. Finally, we introduce new visualizations using the additional information provided by edge maps to indicate the uncertainty involved in computing streamlines and topological structures.

The broad goals of verifiable visualization rely on correct algorithmic implementations. We extend a framework for verification of isosurfacing implementations to check topological properties. Specifically, we use stratified Morse theory and digital topology to design algorithms which verify topological invariants. Our extended framework reveals unexpected behavior and coding mistakes in popular publicly available isosurface codes.

We consider the problem of extracting discrete two-dimensional vortices from a turbulent flow. In our approach we use a reference model describing the expected physics and geometry of an idealized vortex. The model allows us to derive a novel correlation between the size of the vortex and its strength, measured as the square of its strain minus the square of its vorticity. For vortex detection in real models we use the strength parameter to locate potential vortex cores, then measure the similarity of our ideal analytical vortex and the real vortex core for different strength thresholds. This approach provides a metric for how well a vortex core is modeled by an ideal vortex. Moreover, this provides insight into the problem of choosing the thresholds that identify a vortex. By selecting a target coefficient of determination (i.e., statistical confidence), we determine on a per-vortex basis what threshold of the strength parameter would be required to extract that vortex at the chosen confidence. We validate our approach on real data from a global ocean simulation and derive from it a map of expected vortex strengths over the global ocean., (© 2011 IEEE)

Large observations and simulations in scientific research give rise to high-dimensional data sets that present many challenges and opportunities in data analysis and visualization. Researchers in application domains such as engineering, computational biology, climate study, imaging and motion capture are faced with the problem of how to discover compact representations of high-dimensional data while preserving their intrinsic structure. In many applications, the original data is projected onto low-dimensional space via dimensionality reduction techniques prior to modeling. One problem with this approach is that the projection step in the process can fail to preserve structure in the data that is only apparent in high dimensions. Conversely, such techniques may create structural illusions in the projection, implying structure not present in the original high-dimensional data. Our solution is to utilize topological techniques to recover important structures in high-dimensional data that contains non-trivial topology. Specifically, we are interested in high-dimensional branching structures. We construct local circle-valued coordinate functions to represent such features. Subsequently, we perform dimensionality reduction on the data while ensuring such structures are visually preserved. Additionally, we study the effects of global circular structures on visualizations. Our results reveal never-before-seen structures on real-world data sets from a variety of applications., (© 2011 IEEE)

We present a new framework for feature-based statistical analysis of large-scale scientific data and demonstrate its effectiveness by analyzing features from Direct Numerical Simulations (DNS) of turbulent combustion. Turbulent flows are ubiquitous and account for transport and mixing processes in combustion, astrophysics, fusion, and climate modeling among other disciplines. They are also characterized by coherent structure or organized motion, i.e. nonlocal entities whose geometrical features can directly impact molecular mixing and reactive processes. While traditional multi-point statistics provide correlative information, they lack nonlocal structural information, and hence, fail to provide mechanistic causality information between organized fluid motion and mixing and reactive processes. Hence, it is of great interest to capture and track flow features and their statistics together with their correlation with relevant scalar quantities, e.g. temperature or species concentrations. In our approach we encode the set of all possible flow features by pre-computing merge trees augmented with attributes, such as statistical moments of various scalar fields, e.g. temperature, as well as length-scales computed via spectral analysis. The computation is performed in an efficient streaming manner in a pre-processing step and results in a collection of meta-data that is orders of magnitude smaller than the original simulation data. This meta-data is sufficient to support a fully flexible and interactive analysis of the features, allowing for arbitrary thresholds, providing per-feature statistics, and creating various global diagnostics such as Cumulative Density Functions (CDFs), histograms, or time-series. We combine the analysis with a rendering of the features in a linked-view browser that enables scientists to interactively explore, visualize, and analyze the equivalent of one terabyte of simulation data. We highlight the utility of this new framework for combustion science; however, it is applicable to many other science domains., (© 2011 IEEE)

Large-scale simulations are increasingly being used to study complex scientific and engineering phenomena. As a result, advanced visualization and data analysis are also becoming an integral part of the scientific process. Often, a key step in extracting insight from these large simulations involves the definition, extraction, and evaluation of features in the space and time coordinates of the solution. However, in many applications, these features involve a range of parameters and decisions that will affect the quality and direction of the analysis. Examples include particular level sets of a specific scalar field, or local inequalities between derived quantities. A critical step in the analysis is to understand how these arbitrary parameters/decisions impact the statistical properties of the features, since such a characterization will help to evaluate the conclusions of the analysis as a whole. We present a new topological framework that in a single-pass extracts and encodes entire families of possible features definitions as well as their statistical properties. For each time step we construct a hierarchical merge tree a highly compact, yet flexible feature representation. While this data structure is more than two orders of magnitude smaller than the raw simulation data it allows us to extract a set of features for any given parameter selection in a postprocessing step. Furthermore, we augment the trees with additional attributes making it possible to gather a large number of useful global, local, as well as conditional statistic that would otherwise be extremely difficult to compile. We also use this representation to create tracking graphs that describe the temporal evolution of the features over time. Our system provides a linked-view interface to explore the time-evolution of the graph interactively alongside the segmentation, thus making it possible to perform extensive data analysis in a very efficient manner. We demonstrate our framework by extracting and analyzing burning cells from a large-scale turbulent combustion simulation. In particular, we show how the statistical analysis enabled by our techniques provides new insight into the combustion process.

An important goal of scientific data analysis is to understand the behavior of a system or process based on a sample of the system. In many instances it is possible to observe both input parameters and system outputs, and characterize the system as a high-dimensional function. Such data sets arise, for instance, in large numerical simulations, as energy landscapes in optimization problems, or in the analysis of image data relating to biological or medical parameters. This paper proposes an approach to analyze and visualizing such data sets. The proposed method combines topological and geometric techniques to provide interactive visualizations of discretely sampled high-dimensional scalar fields. The method relies on a segmentation of the parameter space using an approximate Morse-Smale complex on the cloud of point samples. For each crystal of the Morse-Smale complex, a regression of the system parameters with respect to the output yields a curve in the parameter space. The result is a simplified geometric representation of the Morse-Smale complex in the high dimensional input domain. Finally, the geometric representation is embedded in 2D, using dimension reduction, to provide a visualization platform. The geometric properties of the regression curves enable the visualization of additional information about each crystal such as local and global shape, width, length, and sampling densities. The method is illustrated on several synthetic examples of two dimensional functions. Two use cases, using data sets from the UCI machine learning repository, demonstrate the utility of the proposed approach on real data. Finally, in collaboration with domain experts the proposed method is applied to two scientific challenges. The analysis of parameters of climate simulations and their relationship to predicted global energy flux and the concentrations of chemical species in a combustion simulation and their integration with temperature.

This paper presents topology-based methods to robustly extract, analyze, and track features defined as subsets of isosurfaces. First, we demonstrate how features identified by thresholding isosurfaces can be defined in terms of the Morse complex. Second, we present a specialized hierarchy that encodes the feature segmentation independent of the threshold while still providing a flexible multiresolution representation. Third, for a given parameter selection, we create detailed tracking graphs representing the complete evolution of all features in a combustion simulation over several hundred time steps. Finally, we discuss a user interface that correlates the tracking information with interactive rendering of the segmented isosurfaces enabling an in-depth analysis of the temporal behavior. We demonstrate our approach by analyzing three numerical simulations of lean hydrogen flames subject to different levels of turbulence. Due to their unstable nature, lean flames burn in cells separated by locally extinguished regions. The number, area, and evolution over time of these cells provide important insights into the impact of turbulence on the combustion process. Utilizing the hierarchy, we can perform an extensive parameter study without reprocessing the data for each set of parameters. The resulting statistics enable scientists to select appropriate parameters and provide insight into the sensitivity of the results with respect to the choice of parameters. Our method allows for the first time to quantitatively correlate the turbulence of the burning process with the distribution of burning regions, properly segmented and selected. In particular, our analysis shows that counterintuitively stronger turbulence leads to larger cell structures, which burn more intensely than expected. This behavior suggests that flames could be stabilized under much leaner conditions than previously anticipated.

This paper introduces an efficient algorithm for computing the Reeb graph of a scalar function f defined on a volumetric mesh M in R3. We introduce a procedure called "loop surgery" that transforms M into a mesh M' by a sequence of cuts and guarantees the Reeb graph of f(M') to be loop free. Therefore, loop surgery reduces Reeb graph computation to the simpler problem of computing a contour tree, for which well-known algorithms exist that are theoretically efficient (O(n log n)) and fast in practice. Inverse cuts reconstruct the loops removed at the beginning. The time complexity of our algorithm is that of a contour tree computation plus a loop surgery overhead, which depends on the number of handles of the mesh. Our systematic experiments confirm that for real-life data, this overhead is comparable to the computation of the contour tree, demonstrating virtually linear scalability on meshes ranging from 70 thousand to 3.5 million tetrahedra. Performance numbers show that our algorithm, although restricted to volumetric data, has an average speedup factor of 6,500 over the previous fastest techniques, handling larger and more complex data-sets.We demonstrate the versatility of our approach by extending fast topologically clean iso surface extraction to non simply-connected domains. We apply this technique in the context of pressure analysis for mechanical design. In this case, our technique produces results in matter of seconds even for the largest meshes. For the same models, previous Reeb graph techniques do not produce a result.

The Morse-Smale (MS) complex has proven to be a useful tool in extracting and visualizing features from scalar-valued data. However, efficient computation of the MS complex for large scale data remains a challenging problem. We describe a new algorithm and easily extensible framework for computing MS complexes for large scale data of any dimension where scalar values are given at the vertices of a closure-finite and weak topology (CW) complex, therefore enabling computation on a wide variety of meshes such as regular grids, simplicial meshes, and adaptive multiresolution (AMR) meshes. A new divide-and-conquer strategy allows for memory-efficient computation of the MS complex and simplification on-the-fly to control the size of the output. In addition to being able to handle various data formats, the framework supports implementation-specific optimizations, for example, for regular data. We present the complete characterization of critical point cancellations in all dimensions. This technique enables the topology based analysis of large data on off-the-shelf computers. In particular we demonstrate the first full computation of the MS complex for a 1 billion/1024(3) node grid on a laptop computer with 2Gb memory.

The Morse-Smale complex is an efficient representation of the gradient behavior of a scalar function, and critical points paired by the complex identify topological features and their importance. We present an algorithm that constructs the Morse-Smale complex in a series of sweeps through the data, identifying various components of the complex in a consistent manner. All components of the complex, both geometric and topological, are computed, providing a complete decomposition of the domain. Efficiency is maintained by representing the geometry of the complex in terms of point sets.

Analysis of the results obtained from material simulations is important in the physical sciences. Our research was motivated by the need to investigate the properties of a simulated porous solid as it is hit by a projectile. This paper describes two techniques for the generation of distance fields containing a minimal number of topological features, and we use them to identify features of the material. We focus on distance fields defined on a volumetric domain considering the distance to a given surface embedded within the domain. Topological features of the field are characterized by its critical points. Our first method begins with a distance field that is computed using a standard approach, and simplifies this field using ideas from Morse theory. We present a procedure for identifying and extracting a feature set through analysis of the MS complex, and apply it to find the invariants in the clean distance field. Our second method proceeds by advancing a front, beginning at the surface, and locally controlling the creation of new critical points. We demonstrate the value of topologically clean distance fields for the analysis of filament structures in porous solids. Our methods produce a curved skeleton representation of the filaments that helps material scientists to perform a detailed qualitative and quantitative analysis of pores, and hence infer important material properties. Furthermore, we provide a set of criteria for finding the "difference" between two skeletal structures, and use this to examine how the structure of the porous solid changes over several timesteps in the simulation of the particle impact.

Scientific visualization and illustration tools are designed to help people understand the structure and complexity of scientific data with images that are as informative and intuitive as possible. In this context the use of metaphors plays an important role since they make complex information easily accessible by using commonly known concepts. In this paper we propose a new metaphor, called "Topological Landscapes," which facilitates understanding the topological structure of scalar functions. The basic idea is to construct a terrain with the same topology as a given dataset and to display the terrain as an easily understood representation of the actual input data. In this projection from an $n$-dimensional scalar function to a two-dimensional (2D) model we preserve function values of critical points, the persistence (function span) of topological features, and one possible additional metric property (in our examples volume). By displaying this topologically equivalent landscape together with the original data we harness the natural human proficiency in understanding terrain topography and make complex topological information easily accessible.

Topology provides a foundation for the development of mathematically sound tools for processing and exploration of scalar fields. Existing topology-based methods can be used to identify interesting features in volumetric data sets, to find seed sets for accelerated isosurface extraction, or to treat individual connected components as distinct entities for isosurfacing or interval volume rendering. We describe a framework for direct volume rendering based on segmenting a volume into regions of equivalent contour topology and applying separate transfer functions to each region. Each region corresponds to a branch of a hierarchical contour tree decomposition, and a separate transfer function can be defined for it. The novel contributions of our work are 1) a volume rendering framework and interface where a unique transfer function can be assigned to each subvolume corresponding to a branch of the contour tree, 2) a runtime method for adjusting data values to reflect contour tree simplifications, 3) an efficient way of mapping a spatial location into the contour tree to determine the applicable transfer function, and 4) an algorithm for hardware-accelerated direct volume rendering that visualizes the contour tree-based segmentation at interactive frame rates using graphics processing units (GPUs) that support loops and conditional branches in fragment programs.

Unstructured tetrahedral meshes are commonly used in scientific computing to represent scalar, vector, and tensor fields in three dimensions. Visualization of these meshes can be difficult to perform interactively due to their size and complexity. By reducing the size of the data, we can accomplish real-time visualization necessary for scientific analysis. We propose a two-step approach for streaming simplification of large tetrahedral meshes. Our algorithm arranges the data on disk in a streaming, I/O-efficient format that allows coherent access to the tetrahedral cells. A quadric-based simplification is sequentially performed on small portions of the mesh in-core. Our output is a coherent streaming mesh which facilitates future processing. Our technique is fast, produces high quality approximations, and operates out-of-core to process meshes too large for main memory.

We describe a new progressive technique that allows real-time rendering of extremely large tetrahedral meshes. Our approach uses a client-server architecture to incrementally stream portions of the mesh from a server to a client which refines the quality of the approximate rendering until it converges to a full quality rendering. The results of previous steps are re-used in each subsequent refinement, thus leading to an efficient rendering. Our novel approach keeps very little geometry on the client and works by refining a set of rendered images at each step. Our interactive representation of the dataset is efficient, light-weight, and high quality. We present a framework for the exploration of large datasets stored on a remote server with a thin client that is capable of rendering and managing full quality volume visualizations.

When a heavy fluid is placed above a light fluid, tiny vertical perturbations in the interface create a characteristic structure of rising bubbles and falling spikes known as Rayleigh-Taylor instability. Rayleigh-Taylor instabilities have received much attention over the past half-century because of their importance in understanding many natural and man-made phenomena, ranging from the rate of formation of heavy elements in supernovae to the design of capsules for Inertial Confinement Fusion. We present a new approach to analyze Rayleigh-Taylor instabilities in which we extract a hierarchical segmentation of the mixing envelope surface to identify bubbles and analyze analogous segmentations of fields on the original interface plane. We compute meaningful statistical information that reveals the evolution of topological features and corroborates the observations made by scientists. We also use geometric tracking to follow the evolution of single bubbles and highlight merge/split events leading to the formation of the large and complex structures characteristic of the later stages. In particular we (i) Provide a formal definition of a bubble; (ii) Segment the envelope surface to identify bubbles; (iii) Provide a multi-scale analysis technique to produce statistical measures of bubble growth; (iv) Correlate bubble measurements with analysis of fields on the interface plane; (v) Track the evolution of individual bubbles over time. Our approach is based on the rigorous mathematical foundations of Morse theory and can be applied to a more general class of applications.

This paper describes an efficient combinatorial method for simplification of topological features in a 3D scalar function. The Morse-Smale complex, which provides a succinct representation of a function's associated gradient flow field, is used to identify topological features and their significance. The simplification process, guided by the Morse-Smale complex, proceeds by repeatedly applying two atomic operations that each remove a pair of critical points from the complex. Efficient storage of the complex results in execution of these atomic operations at interactive rates. Visualization of the simplified complex shows that the simplification preserves significant topological features while removing small features and noise.

We combine topological and geometric methods to construct a multiresolution representation for a function over a two-dimensional domain. In a preprocessing stage, we create the Morse-Smale complex of the function and progressively simplify its topology by cancelling pairs of critical points. Based on a simple notion of dependency among these cancellations, we construct a hierarchical data structure supporting traversal and reconstruction operations similarly to traditional geometry-based representations. We use this data structure to extract topologically valid approximations that satisfy error bounds provided at runtime.

Three-dimensional (3D) computer reconstruction is an ideal tool for evaluating the centralized pathology of mammalian spinal cord injury (SCI) where multiple anatomical features are embedded within each other. Here, we evaluate three different reconstruction algorithms to three-dimensionally visualize SCIs. We also show for the first time, that determination of the volume and surface area of pathological features is possible using the reconstructed 3D images themselves. We compare these measurements to those calculated by older morphometric approaches. Finally, we demonstrate dynamic navigation into a 3D spinal cord reconstruction.

Purpose: The role of immunoscintigraphy with 111In-satumomab pendetide in the medical and/or surgical management of colorectal cancer patients was evaluated in a multicenter trial., Methods: This 103 patient study population included 46 individuals with rising serum carcinoembryonic antigen levels and otherwise negative diagnostic evaluation, 29 patients with known recurrence, presumed to be isolated and resectable, and 28 patients for whom standard diagnostic tests provided equivocal information., Results: No adverse reactions were noted following intravenous administration of 1 mg of satumomab pendetide radiolabeled with approximately 5 mCi of 111In. Thirty percent of patients developed human anti-mouse antibodies postinfusion. In the 84 patients for whom correlation with histopathologic, diagnostic, and/or clinical findings was available, antibody imaging demonstrated a sensitivity of 73 percent in patients with confirmed tumor (36/49) and negative results for all 35 patients with no evidence of malignancy. Occult disease was detected in 18 patients., Conclusion: 111In-satumomab pendetide immunoscintigraphy was helpful in the medical and/or surgical management of 45 (44 percent) patients and provided information unavailable from other diagnostic modalities.

Application of monoclonal antibody (MoAb) technology to cancer management is discussed by reviewing the development and clinical evaluation of two MoAb-based immunoscintigraphic agents (111In-satumomab pendetide [OncoScint CR/OV-In] and 111In-CYT-356; Cytogen Corporation, Princeton, NJ). Both agents were prepared using a site-specific MoAb modification method that preserves the immunoreactivity of the radiolabeled immunoconjugate. 111In-satumomab pendetide is an 111In-labeled conjugate of the murine MoAb B72.3, which is directed to TAG-72, an antigen expressed by the majority of adenocarcinomas. By providing information that complements the results of standard radiographic diagnostic modalities, this imaging agent can aid in the treatment of patients with colorectal or ovarian cancer. Immunoscintigraphy with 111In-satumomab pendetide has been shown to assist in medical-surgical management by detecting occult extrahepatic lesions, clarifying equivocal results of other diagnostic imaging tests, and evaluating the extent and resectability of known tumor lesions. 111In-CYT-356 is an 111In-labeled conjugate of the murine MoAb 7E11-C5.3, which is reactive with prostatic carcinoma, benign prostatic hypertrophy, and, to a lesser extent, normal prostatic tissue. Results of preliminary clinical investigations suggest that 111In-CYT-356 immunoscintigraphy can be useful for the presurgical staging of prostatic carcinoma and for the detection of occult distant disease in patients with negative or equivocal results on standard imaging tests. Results with these site-specifically radiolabeled immunconjugates demonstrate the clinical utility of MoAb-based imaging agents in the treatment of patients with solid tumors.

The antihypertensive efficacy and safety of indoramin, an alpha 1-adrenergic antagonist, were evaluated in 215 elderly patients. Data were collected from patients aged 60 years and older who were treated under similar protocols with indoramin administered alone (n = 58) or in combination with a thiazide diuretic (n = 157). After at least 6 months of treatment, the mean daily dosage of indoramin was higher among patients who received indoramin alone (122 mg/day) than among those who received indoramin plus a diuretic (92 mg/day). Mean supine blood pressure decreased (p less than 0.001) from 174/105 to 152/191 mm Hg in indoramin-treated patients and from 179/101 to 150/91 mm Hg in patients who were treated with indoramin plus a diuretic. Clinically satisfactory blood pressure decreases occurred in the majority of the patients who received indoramin, either alone (69%) or with a diuretic (75%). Both treatments were well tolerated by elderly patients; only 15 patients (7%) discontinued therapy because of adverse effects. Drowsiness, fatigue, and dizziness were the most frequently reported side effects. The results of this analysis indicate that indoramin, administered alone or in combination with a thiazide diuretic, is a safe and effective therapeutic regimen for elderly hypertensive patients.

A rapid, specific procedure is described for the quantitation of ketoconazole in biological fluids using high-performance liquid chromatography (HPLC). The procedure involves sample preparation using a reverse-phase C-18 cartridge prior to chromatography and quantitation using peak height ratios (UV absorbance detection, 231 nm) of ketoconazole to the internal standard, phenothiazine. A sensitivity of 0.2 micrograms/ml was achieved using a 0.5-ml sample. The mean recovery was 86.2%, and overall coefficient of variation of the procedure was 7.1%. This procedure has been used to determine ketoconazole levels in human serum, plasma, CSF, and synovial fluid. A comparison with a microbiological assay is presented, and adaptability of this procedure to quantitation by fluorescence to increase the sensitivity fivefold is discussed.

A rapid, sensitive, and selective assay is described for the quantitation of both testolactone and its recently identified metabolite, 4,5-dihydrotestolactone, in plasma and urine using high-performance liquid chromatography. The procedure includes a methylene chloride extraction prior to chromatography and quantitation using peak height ratios (ultraviolet absorbance detection, 242 nm) of testolactone and 4,5-dihydrotestolactone to the internal standard, testosterone. A sensitivity of 20 ng/ml for both testolactone and 4,5-dihydrotestolactone is easily achieved using only 0.5 ml of sample. Mean recoveries for testolactone and its metabolite are 95.0% and 81.8%, respectively, and the mean coefficient of variation of the procedure is 3.5% for the drug and 7.1% for the metabolite. This method is currently being used to study the pharmacokinetics of testolactone and 4,5-dihydrotestolactone in male patients. A steady-state plasma concentration versus time profile from a representative patient is included.

The disposition of guanabenz, a centrally acting antihypertensive agent, was compared in 10 normotensive patients (eight males and two females) with chronic hepatic disease secondary to alcohol abuse and 10 healthy male volunteers after a 16 mg oral dose. Mean plasma concentrations of guanabenz were higher in patients with liver disease than in healthy subjects at every sampling time through 72 h after drug administration (p less than 0.05). In liver disease patients, the mean oral-dose clearance (2 L/h/kg) and terminal-phase volume of distribution (20 L/kg) were lower (p less than 0.001) than the respective values of 11 L/h/kg and 71 L/kg of healthy volunteers. The mean plasma half-life of patients with liver disease (6.4 h) was not significantly longer than that of healthy subjects (4.3 h). The mean fraction of unbound drug in the plasma was higher (p less than 0.01) in patients with liver disease (12.7%) than in healthy volunteers (10.5%). As guanabenz is eliminated predominantly via hepatic biotransformation and undergoes significant presystemic elimination after oral administration, the changes in guanabenz disposition in liver disease are not unexpected. They may be explained by enhanced oral bioavailability, owing to portosystemic shunting and/or reduced intrinsic clearance, combined with decreased hepatic clearance of guanabenz in liver disease. Individual dosage titration may be required when guanabenz is used for antihypertensive therapy of patients with chronic liver disease.

In a multicenter, prospective study of step II antihypertensive therapy with indoramin, 1,847 hypertensive patients (773 men and 1,074 women) between the ages of 18 and 70 years were treated by 148 general practitioners. Patients whose blood pressure was inadequately controlled after 4 weeks of therapy with cyclopenthiazide (0.25 to 1.0 mg/day) had indoramin (25 to 200 mg/day) added to their treatment regimen. During cyclopenthiazide treatment, mean (+/- SD) blood pressure decreased from 176/105 +/- 20/7 mm Hg at baseline to 164/98 +/- 21/9 mm Hg (p less than 0.001), and only 447 (24%) patients obtained satisfactory blood pressure control. The addition of indoramin produced a further reduction in mean blood pressure from 169/102 +/- 18/6 to 152/89 +/- 18/8 mm Hg during the first 3 months of treatment (p less than 0.001); this response was maintained for up to 2 years. Satisfactory blood pressure reduction was achieved in 79% of the patients who received indoramin (mean dose, 68 mg/day) plus cyclopenthiazide. Only 25 patients (2%) discontinued indoramin treatment because of nonresponse, and 156 (12%) withdrew because of adverse effects, the most common being sedation, dizziness/giddiness, and headache. These results indicate that indoramin provides safe and effective blood pressure control when used as step II treatment for hypertensive patients who fail to respond to single-agent diuretic therapy.

The management of hypertension in patients with chronic obstructive pulmonary disease (COPD) may be complicated by the adverse effects of several antihypertensive agents on pulmonary function. The safety and antihypertensive efficacy of guanabenz, a centrally acting alpha-adrenergic agonist, were evaluated in 42 patients with asthma and 24 patients with other forms of COPD. Among the 64 patients with data evaluated for efficacy, pretreatment supine diastolic blood pressures (SDBP) were between 90 and 121 mm Hg (mean, 100 mm Hg). The patients were treated for 6 months with guanabenz as sole antihypertensive therapy in doses ranging from 8 to 64 mg/day (mean final dosage, 28 mg/day). At the end of the treatment period, a mean decrease in SDBP of 10 mm Hg was observed (p less than 0.001). Excellent or satisfactory blood pressure responses were obtained for 65% of the asthmatic patients and 83% of the patients with other forms of COPD. Mean supine pulse rate decreased by 7 beats/min (p less than 0.001), and mean body weight decreased by 2 lb. (p less than 0.05). Only one patient discontinued guanabenz treatment because of an exacerbation of asthma thought to be due to airway dryness. Because beta-adrenergic blocking agents, including the cardioselective drugs, have been known to exacerbate COPD, guanabenz treatment may be preferable as antiadrenergic antihypertensive therapy in patients with asthma and other forms of COPD.

The pharmacokinetics of guanabenz (16 mg) and hydrochlorothiazide (25 mg), administered separately and as a fixed-combination tablet (guanabenz 16 mg/hydrochlorothiazide 25 mg), were compared in a randomized three-period crossover study in 24 healthy men. Plasma concentrations were monitored for 48 h after each administration. No statistically significant differences between the two formulations were noted in mean plasma concentrations or the rate and extent of absorption of guanabenz. The relative bioavailability (Fr) of the combination tablet compared with guanabenz alone was 96%; thus the two formulations were bioequivalent with respect to guanabenz. For hydrochlorothiazide, mean plasma concentrations were similar for 3 h after administration but were higher for the combination tablet than for hydrochlorothiazide alone from 4 through 48 h (p less than 0.05). A significant increase in the extent, but not the rate, of absorption of hydrochlorothiazide was observed for the combination tablet (mean Fr, 120%), which is not considered clinically significant. We propose that this increase may have been due to increased systemic availability of hydrochlorothiazide in the presence of guanabenz, an alpha-adrenergic agonist, which may have delayed intestinal transport of hydrochlorothiazide, resulting in enhanced gastrointestinal absorption.